Big Data and Unemployment Analysis

Mihaela Simionescu and Klaus Zimmermann ()

No 81, GLO Discussion Paper Series from Global Labor Organization (GLO)

Abstract: Internet or "big" data are increasingly measuring the relevant activities of individuals, households, firms and public agents in a timely way. The information set involves large numbers of observations and embraces flexible conceptual forms and experimental settings. Therefore, internet data are extremely useful to study a wide variety of human resource issues including forecasting, nowcasting, detecting health issues and well-being, capturing the matching process in various parts of individual life, and measuring complex processes where traditional data have known deficits. We focus here on the analysis of unemployment by means of internet activity data, a literature starting with the seminal article of Askitas and Zimmermann (2009a). The article provides insights and a brief overview of the current state of research.

Keywords: big data; unemployment; internet; Google; internet penetration rate (search for similar items in EconPapers)
JEL-codes: C22 C82 E17 E24 E37 (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-big, nep-ltv and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:glodps:81

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